Model-based Diagnosis of a Satellite Electrical Power System woth RODON
As space exploration vehicles travel deeper into space, their distance
to earth increases. The increased communication delays and ground
personnel costs motivate a migration of the vehicle health management
into space. A way to achieve this is to use a diagnosis system. A
diagnosis system uses sensor readings to automatically detect faults
and possibly locate the cause of it. The diagnosis system used in this
thesis is a model-based reasoning tool called RODON developed by
Uptime Solutions AB. RODON uses information of both nominal and faulty
behavior of the target system mathematically formulated in a model.
The advanced diagnostics and prognostics testbed (ADAPT) developed at
the NASA Ames Research Center provides a stepping stone between pure
research and deployment of diagnosis and prognosis systems in
aerospace systems. The hardware of the testbed is an electrical power
system (EPS) that represents the EPS of a space exploration
vehicle. ADAPT consists of a controlled and monitored environment
where faults can be injected into a system in a controlled manner and
the performance of the diagnosis system carefully monitored. The main
goal of the thesis project was to build a model of the ADAPT EPS that
was used to diagnose the testbed and to generate decision trees (or
trouble-shooting trees).
The results from the diagnostic analysis were good and all injected
faults that affected the actual function of the EPS were detected. All
sensor faults were detected except faults in temperature sensors. A
less detailed model would have isolated the correct faulty
component(s) in the experiments. However, the goal was to create a
detailed model that can detect more than the faults currently injected
into ADAPT. The created model is stationary but a dynamic model would
have been able to detect faults in temperature sensors.
Based on the presented results, RODON is very well suited for
stationary analysis of large systems with a mixture of continuous and
discrete signals. It is possible to get very good results using RODON
but in turn it requires an equally good model. A full analysis of the
dynamic capabilities of RODON was never conducted in the thesis which
is why no conclusions can be drawn for that case.
Olle Isaksson
2009
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Senast uppdaterad: 2021-11-10
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